PROJECT SUMMARY/ABSTRACT Kawasaki Disease (KD) is a major contributor to cardiovascular morbidity in children. Poor response to IVIG remains one of the critical determinants of coronary artery risk in KD. The inability to predict this response and the potential for developing persistent coronary artery aneurysms serves as a major impediment to progress and development of intensified therapy. Currently available data indicate that KD susceptibility and treatment response, as well as the propensity for coronary artery disease, depend on an individual patient's genetic background. Studies directed at identifying appropriate genetic biomarkers have been impaired by: 1) phenotyping lacking rigor, 2) use of genome wide association studies often employing chips or arrays for detection of common variants rather than low frequency or rare variants, 3) lack of clarity for the mechanisms of IVIG anti-inflammation in KD (necessary for guiding most pharmacogenomics studies) 4) focus on gene candidates, which are impractical for clinical testing, and 5) vague racial assignment methodology confounding pharmacogenomics. Furthermore, exome sequencing and analyses likely would miss potential important variants as IVIG anti-inflammatory mechanism includes transcriptional regulation at intergenic regions. We hypothesize that, by using improved and rigorous phenotyping techniques in combination with whole genome sequencing (WGS) and analyses, we will be able to identify select biomarkers for accurate prediction of KD treatment response and development of coronary aneurysms. The Pacific Northwest Kawasaki Disease Data-Biobank, established mainly through funding via PI Portman, R21HL090558, Thrasher Research Foundation; and PI, Shrestha, Southeastern AHA has accumulated DNA and clinical data from over 800 KD patients, eligible for pharmacogenomics analyses. We will leverage this wealth of DNA and clinical data along with recently updated AHA clinical KD criteria in order to identify rare and common variants, which determine IVIG treatment response. WGS will also allow a) identification of individual private SNPs (rare variants), b) identification of population-specific private SNPs, c) building a complete picture of genetic variations including structural variants (CNVs and insertion/deletions), d) gene- based analysis of both common and rare variants, and e) identification of actual functional SNPs as opposed to common imputed or SNPs in linkage disequilibrium (LD). Additionally, we will account for race, an important variant in KD, by rigorous racial assignment using ancestry information markers and principal component analyses. We will use rigorous methodology to achieve the following specific aims 1) Perform whole genome sequencing to identify genetic variations, which could serve as clinical biomarkers for IVIG resistance in KD patients. 2) Determine novel genomic variants associated with giant coronary artery aneurysms (GCA) among children with KD. 3) Prepare to assess if IVIG resistance is greater among African Americans and if this response depends on racial based differences in the frequency of genetic variations.